The course begins by covering relevant applications of spatial computing. It then focuses on theoretical background spatial objects, spatial operations, spatial access methods topics and spatial statistics. In labs two broad approaches for management and analysis of a spa tial data are introduced. The first utilizes database technologies (specifically, the Postgres database management system and its spatial extension PostGIS); the second utilizes programming languages (R and Python packages for spatial analysis). At the last, the course introduces big spatial frameworks (HadoopGIS, Geospark).
Spatial Data Science by S. Shekar
Spatial Access Methods
Geostatistics and Spatial Statistics
Big Data Frameworks: HadoopGIS and GeoSpark
Labs: Spatial Analysis with R • PostGIS -PostgreSQL GIS Extension • pgRouting • QGIS
Textbooks:
+ Sashi Shekhar and Sanjay Chawla: Spatial Databases: A Tour. Pearson Eds. 2003.
+ Chris Brunsdon and Lex Comber: An Introduction to R for Spatial Analysis and Mapping SAGE Publications, 2015.
+ Dominik Mikiewicz, Michal Mackiewicz, Tomasz Nycz: Mastering PostGIS, Packt Pubs, 2017.